Finding the signal in the noise: Could social media be utilized for early hospital notification of multiple casualty events?
| Title: | Finding the signal in the noise: Could social media be utilized for early hospital notification of multiple casualty events? |
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| Authors: | Rachael A Callcut, Sara Moore, Glenn Wakam, Alan E Hubbard, Mitchell J Cohen |
| Source: | PLoS ONE, Vol 12, Iss 10, p e0186118 (2017) |
| Publisher Information: | Public Library of Science (PLoS), 2017. |
| Publication Year: | 2017 |
| Collection: | LCC:Medicine LCC:Science |
| Subject Terms: | Medicine, Science |
| More Details: | Delayed notification and lack of early information hinder timely hospital based activations in large scale multiple casualty events. We hypothesized that Twitter real-time data would produce a unique and reproducible signal within minutes of multiple casualty events and we investigated the timing of the signal compared with other hospital disaster notification mechanisms.Using disaster specific search terms, all relevant tweets from the event to 7 days post-event were analyzed for 5 recent US based multiple casualty events (Boston Bombing [BB], SF Plane Crash [SF], Napa Earthquake [NE], Sandy Hook [SH], and Marysville Shooting [MV]). Quantitative and qualitative analysis of tweet utilization were compared across events.Over 3.8 million tweets were analyzed (SH 1.8 m, BB 1.1m, SF 430k, MV 250k, NE 205k). Peak tweets per min ranged from 209-3326. The mean followers per tweeter ranged from 3382-9992 across events. Retweets were tweeted a mean of 82-564 times per event. Tweets occurred very rapidly for all events ( |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1932-6203 59705604 |
| Relation: | http://europepmc.org/articles/PMC5628942?pdf=render; https://doaj.org/toc/1932-6203 |
| DOI: | 10.1371/journal.pone.0186118 |
| Access URL: | https://doaj.org/article/ab597056045748778e8cbdfa5ac74872 |
| Accession Number: | edsdoj.b597056045748778e8cbdfa5ac74872 |
| Database: | Directory of Open Access Journals |
| ISSN: | 19326203 59705604 |
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| DOI: | 10.1371/journal.pone.0186118 |
| Published in: | PLoS ONE |
| Language: | English |